Business Directory Scraper with Selenium

The aim of this project was to create a versatile command-line web scraping tool that could efficiently extract data from an online business directory website. The website, characterized by its dynamic nature, required interactions such as clicking and scrolling to access and collect valuable business information.

Python (Pandas, Requests, BeautifulSoup)

Selenium WebDriver

The website being scraped required various interactions to access hidden data. To overcome this challenge, we implemented Selenium, a web automation tool. It allowed us to simulate user actions, such as clicking on buttons and scrolling down, ensuring we retrieved all relevant data.

We designed the tool to have a user-friendly command-line interface. This allowed the user to easily specify input parameters, such as the category name from the business directory that needs to be scraped.

Using Selenium, we navigated through the web pages, locating and extracting data such as business names, addresses, descriptions, keywords, contact details, website and other relevant details. The scraped data was stored in an organized manner for further processing.

The dynamic nature of the business directory made it challenging to scrape data efficiently. Using Selenium's capabilities to mimic user interactions was key to addressing this challenge.

We implemented robust error handling mechanisms to account for potential issues like page load failures, element not found errors or unexpected website changes. This ensured the tool's reliability.

Scraping a large dataset from a dynamic website can be time-consuming. We optimized the tool to maximize performance and minimize the time required to complete the scraping process.

The tool successfully met its objectives. The client could easily extract data from the business directory by entering a simple command in the terminal. This tool saved the client's valuable time and provided him with structured data ready for actionable insights.